Mining Urban Perceptions from Social Media Data
| dc.contributor.author | Liu, Yu | |
| dc.contributor.author | Yuan, Yihong | |
| dc.contributor.author | Zhang, Fan | |
| dc.date.accessioned | 2020-07-22T18:24:32Z | |
| dc.date.available | 2020-07-22T18:24:32Z | |
| dc.date.issued | 2020-04 | |
| dc.description.abstract | This vision paper summaries the methods of using social media data (SMD) to measure urban perceptions. We highlight two major types of data sources (i.e., texts and imagery) and two corresponding techniques (i.e., natural language processing and computer vision). Recognizing the data quality issues of SMD, we propose three criteria for improving the reliability of SMD-based studies. In addition, integrating multi-source data is a promising approach to mitigating the data quality problems. | |
| dc.description.department | Geography and Environmental Studies | |
| dc.format | Text | |
| dc.format.extent | 6 pages | |
| dc.format.medium | 1 file (.pdf) | |
| dc.identifier.citation | Liu, Y., Yuan, Y., & Zhang, F. (2020). Mining urban perceptions from social media data. Journal of Spatial Information Science, 2020(20), pp. 51–55. | |
| dc.identifier.doi | https://doi.org/10.5311/JOSIS.2020.20.665 | |
| dc.identifier.issn | 1948-660X | |
| dc.identifier.uri | https://hdl.handle.net/10877/12143 | |
| dc.language.iso | en | |
| dc.publisher | University of Maine | |
| dc.rights.holder | © 2020 The Authors. | |
| dc.rights.license | This work is licensed under a Creative Commons Attribution 3.0 Unported License. | |
| dc.source | Journal of Spatial Information Science, 2020, No. 20, pp. 51–55. | |
| dc.subject | urban perceptions | |
| dc.subject | place | |
| dc.subject | data quality | |
| dc.subject | natural language processing | |
| dc.subject | computer vision | |
| dc.subject | social media data | |
| dc.subject | Geography and Environmental Studies | |
| dc.title | Mining Urban Perceptions from Social Media Data | |
| dc.type | Article |